DBMS > Citus vs. Spark SQL vs. SQLite vs. SWC-DB vs. TigerGraph

System Properties Comparison Citus vs. Spark SQL vs. SQLite vs. SWC-DB vs. TigerGraph

Editorial information provided by DB-Engines

Name

Description

Scalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQL

Spark SQL is a component on top of 'Spark Core' for structured data processing

Widely used embeddable, in-process RDBMS

A high performance, scalable Wide Column DBMS

A complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time

Primary database model

Relational DBMS

Wide column store

Graph DBMS

Secondary database models

Document store

Time Series DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	2.21
Rank	#118	Overall
	#56	Relational DBMS

Score	18.96
Rank	#33	Overall
	#20	Relational DBMS

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

Score	0.01
Rank	#376	Overall
	#13	Wide column stores

Score	1.83
Rank	#139	Overall
	#13	Graph DBMS

Website

www.citusdata.com

spark.apache.org/sql

www.sqlite.org

github.com/kashirin-alex/swc-db
www.swcdb.org

www.tigergraph.com

Technical documentation

docs.citusdata.com

spark.apache.org/docs/latest/sql-programming-guide.html

www.sqlite.org/docs.html

docs.tigergraph.com

Developer

Apache Software Foundation

Dwayne Richard Hipp

Alex Kashirin

Initial release

2010

2014

2000

2020

2017

Current release

8.1, December 2018

3.5.0 ( 2.13), September 2023

3.45.3 (15 April 2024), April 2024

0.5, April 2021

License

Commercial or Open Source

Open Source

AGPL, commercial license also available

Open Source

Apache 2.0

Open Source

Public Domain

Open Source

GPL V3

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Scala

C++

Server operating systems

Linux

Linux
OS X
Windows

server-less

Linux

Data scheme

yes

dynamic column types

schema-free

yes

Typing

predefined data types such as float or date

yes

not rigid because of 'dynamic typing' concept.

yes

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

yes

specific XML type available, but no XML query functionality

Secondary indexes

yes

SQL

Support of SQL

yes

standard, with numerous extensions

SQL-like DML and DDL statements

yes

SQL-92 is not fully supported

SQL-like query language

SQL-like query language (GSQL)

APIs and other access methods

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

JDBC
ODBC

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Proprietary protocol
Thrift

GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API

Supported programming languages

.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Java
Python
R
Scala

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

C++

C++
Java

Server-side scripts

Stored procedures

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes, utilizing Spark Core

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

other methods possible by using 3rd party extensions

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

yes

Durability

Support for making data persistent

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Role-based access control

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